The escalation of violence in Mexico and along the border with the United States has triggered a number of social responses that attempt both to control and to live with current levels of uncertainty in both countries. Additionally, several other social problems have contributed to the messiness of the current situation making it difficult for individuals and governments to identify leverage points of intervention. This work explores dynamic drivers of the emergence of violence in Mexico and along the border with the United States as a specific manifestation of the social processes that turn illegality into instability. A system dynamics approach is used to explore these issues in an effort to identify high-leverage points of intervention.
Finding the difficulties and concerns of the client, understanding the variables involved in creating the difficulties, exploring the casualty amongst the identified variables and framing the dynamic hypothesis is the most critical and difficult phase of system dynamics modeling process. Although, there are many ideas in literature to carry out this phase, lack of a comprehensive qualitative method is noticeable. Hence, the authors of current paper, by reviewing the literature, introduce an inclusive and customized grounded theory method, specific to requirements of qualitative system dynamics modeling. Additionally, this paper argues that the methodology described in the paper could contribute to integrating of existing methodologies, facilitating the iterative process of modeling and set up a systematic framework in order to maintain and relate findings of qualitative phase to quantitative phase in system dynamics modeling process.
Capital asset replacement has a significant effect on company cash flow, since the investment on new asset is expensive. Overhaul policy can extend the optimal service life of an asset, and results in lower total life cycle cost of an asset. Technological change also affects the life cycle cost and optimal service life of an asset. In this paper we examine the replacement/renewal and overhaul/refurbish policies in a combination under technological change. We used System Dynamics model and simulate hypothetical data for 4 cases, and the output is in line with some previous studies using analytical models.
Tourism is a dynamic and complex system, which involves numerous stakeholders, each with different understandings of the system and holding different management objectives. These different expectations result in unforeseen conflicts among stakeholders that could negatively affect the development of tourism. This paper describes a participatory systems approach to develop a shared understanding amongst stakeholders of the tourism system in the UNESCO designated Cat Ba Biosphere Reserve in Vietnam.
Article describes the complex of imitation models of social sphere. The model complex is intended for support of decision-making in social sphere, focusing on problems of reforming of housing, public health services and social security. The complex is realized on the basis of system dynamics methods and modern technologies of simulation modeling.
In the political violence scholarship, there is a gap in explaining how group-level dynamics cause mass political violence. There are several theories of why political groups become violent. Because of the qualitative nature of these theories and the feedback complexity of political violence, it is hard to test these theories against each other and against data. This paper describes an attempt to use a combination of system dynamics and agent-based modeling to create a simulation pitting rival theories of political violence against each other and against empirical data. The purpose of the research is theory testing: to see what theory or combination of theories best explains political violence. The paper provides an overview of the relevant theory and data. The paper then develops a dynamic hypothesis and a prototype hybrid Netlogo simulation of two theories, political opportunity and collective action.
Out of Stock (OOS) has long been a plaguing problem in the consumer packaged goods (CPG) industry for both manufacturers and retailers. It refers to a situation in which an item is unavailable for sale as intended at a store. One study estimated that OOS items on average cost retailers 4 percent of their annual sales, and manufacturers $23 million for every $1 billion in sales. OOS could be caused by many factors, such as manufacturer production shortage, distribution center delay, consumer demand surge, and sub-optimal store operations, etc. There have been many previous attempts to model and fix OOS. To the authors knowledge, this is the first study to address the full production-distribution system using system dynamics (SD) and help all players understand the structure of the CPG distribution system that contributes to the system behavior that causes OOS, and interventions or improvements that can be made to the system to improve its performance related to OOS events. This paper will describe the OOS model we developed, the insights we gained, and the process we used to translate the initial SD model into a business application that can be employed on a wide range of product and retailer scenarios.